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Auto-DSM: Using a Large Language Model to generate a Design Structure Matrix

Authors :
Edwin C.Y. Koh
Source :
Natural Language Processing Journal, Vol 9, Iss , Pp 100103- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

The Design Structure Matrix (DSM) is an established method used in dependency modelling, especially in the design of complex engineering systems. The generation of DSM is traditionally carried out through manual means and can involve interviewing experts to elicit critical system elements and the relationships between them. Such manual approaches can be time-consuming and costly. This paper presents a workflow that uses a Large Language Model (LLM) to support the generation of DSM and improve productivity. A prototype of the workflow was developed in this work and applied on a diesel engine DSM published previously. It was found that the prototype could reproduce 357 out of 462 DSM entries published (i.e. 77.3%), suggesting that the work can aid DSM generation. A no-code version of the prototype is made available online to support future research.

Details

Language :
English
ISSN :
29497191
Volume :
9
Issue :
100103-
Database :
Directory of Open Access Journals
Journal :
Natural Language Processing Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.fc6d8b7498743a8995b8ea9323e783b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.nlp.2024.100103